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Clinical laboratory medicine measurements correlation analysis under uncertainty
1Department of Statistics, Faculty of Science, 37848King Abdulaziz University, Jeddah, Saudi Arabia.
Annals of Clinical Biochemistry
|March 18, 2021
Summary
A new neutrosophic statistics Spearman rank correlation test enhances data analysis for interval or indeterminate paired data. This advanced method offers greater efficiency and applicability in clinical settings compared to classical statistics.
Area of Science:
- Statistics
- Neutrosophic Statistics
- Correlation Analysis
Background:
- Classical Spearman rank correlation test limitations with interval or indeterminate paired data.
- Need for a more robust statistical method for such data types.
Purpose of the Study:
- Introduce a generalized Spearman rank correlation test using neutrosophic statistics.
- Enhance the analysis of measurement data, particularly in indeterminate environments.
Main Methods:
- Development of a Spearman rank correlation test under neutrosophic statistics.
- Generalization of the existing Spearman rank correlation test.
Main Results:
- The proposed neutrosophic test is more informative, flexible, and adequate for measurement data analysis.
- Application to luteotropichormone data showed a 69% indeterminacy rate.
- The neutrosophic test demonstrated higher efficiency in managing indeterminacy.
Conclusions:
- The neutrosophic Spearman rank correlation test is superior to classical methods in indeterminate environments.
- Recommended for clinical laboratories to test correlations between instruments.
- Offers improved applicability and usability for complex data analysis.
Keywords:
Spearman rank correlation testclassical statisticshypothesisindeterminacymeasurement dataneutrosophic statisticsneutrosophyMore Related Videos
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